DATA MODELS
14-1 INTRODUCTION
Data storage traditionally used individual, unrelated
files, sometimes called flat files. In the past, each
application program in an organization used its own file.
In a university, for example, each department might
have its own set of files: the record office kept a file
about the student information and their grades, the
scheduling office kept the name of the professors and
the courses they were teaching, the payroll department
kept its own file about the whole staff and so on. Today,
however, all of these flat files can be combined in a
single entity; the database for the whole university.
14.2
Definition
Although it is difficult to give a universally agreed definition
of a database, we use the following common definition:
i
Definition:
A database is a collection of related, logically coherent
data used by the application
programs in an organization.
14.3
Advantages of databases
Comparing the flat-file system, we can mention several
advantages for a database system.
Less redundancy
In a flat-file system there is a lot of redundancy. For
example, in the flat file system for a university, the names of
professors and students are stored in more than one file.
Inconsistency avoidance
If the same piece of information is stored in more than one
place, then any changes in the data need to occur in all places
that data is stored.
14.4
Efficiency
A database is usually more efficient that a flat file system,
because a piece of information is stored in fewer locations.
Data integrity
In a database system it is easier to maintain data integrity
(see Chapter 16), because a piece of data is stored in fewer
locations.
Confidentiality
It is easier to maintain the confidentiality of the information
if the storage of data is centralized in one location.
14.5
14-2 DATABASE MANAGEMENT SYSTEMS
A database management system (DBMS) defines,
creates and maintains a database. The DBMS also
allows controlled access to data in the database. A
DBMS is a combination of five components: hardware,
software, data, users and procedures (Figure 14.1).
14.6
Figure 14.1 DBMS components
Hardware
The hardware is the physical computer system that allows
access to data.
Software
The software is the actual program that allows users to
access, maintain and update data. In addition, the software
controls which user can access which parts of the data in the
database.
Confidentiality
The data in a database is stored physically on the storage
devices. In a database, data is a separate entity from the
software that accesses it.
14.7
Users
In a DBMS, the term users has a broad meaning. We can
divide users into two categories: end users and application
programs.
Procedures
The last component of a DBMS is a set of procedures or
rules that should be clearly defined and followed by the users
of the database.
14.8
14-3 DATABASE ARCHITECTURE
The American National Standards Institute/Standards
Planning and Requirements Committee (ANSI/SPARC)
has established a three-level architecture for a DBMS:
internal, conceptual and external (Figure 14.2).
14.9
Figure 14.2 Database architecture
14.10
Internal level
The internal level determines where data is actually stored on
the storage devices. This level deals with low-level access
methods and how bytes are transferred to and from storage
devices. In other words, the internal level interacts directly
with the hardware.
Conceptual level
The conceptual level defines the logical view of the data.
The data model is defined on this level, and the main
functions of the DBMS, such as queries, are also on this
level. The DBMS changes the internal view of data to the
external view that users need to see. The conceptual level is
an intermediary and frees users from dealing with the
internal
level.
14.11
External level
The external level interacts directly with the user (end users
or application programs). It changes the data coming from
the conceptual level to a format and view that is familiar to
the users.
14.12
DATA MODELS
Data model tells how the logical structure of a
database is modeled. Data Models are
fundamental entities to introduce abstraction in
DBMS. Data models define how data is connected
to each other and how it will be processed and
stored inside the system.
14-4 DATABASE MODELS
A database model defines the logical design of data. The
model also describes the relationships between different
parts of the data. In the history of database design, three
models have been in use: the hierarchical model, the
network model and the relational model.
14.14
Hierarchical Model
•
In a hierarchical model data is organized into a tree-like structure implying a
single parent for each record. A sort field keeps sibling records in a particular
order. Hierarchical structures were widely used in the early mainframe database
management systems, such as the Information Management System (IMS) by IBM,
•
This structure allows one one-to-many relationship between two types of data.
This structure is very efficient to describe many relationships in the real world;
recipes, table of contents, ordering of paragraphs/verses, any nested and sorted
information.
This hierarchy is used as the physical order of records in storage. Record access is
done by navigating through the data structure using pointers combined with
sequential accessing. Because of this, the hierarchical structure is inefficient for
certain database operations when a full path (as opposed to upward link and sort
field) is not also included for each record. Such limitations have been
compensated for in later IMS versions by additional logical hierarchies imposed
on the base physical hierarchy.
•
The hierarchical data model
•
The hierarchical data model organizes data in a tree structure. There is a hierarchy
of parent and child data segments. This structure implies that a record can have
repeating information, generally in the child data segments. Data in a series of
records, which have a set of field values attached to it. It collects all the instances
of a specific record together as a record type. These record types are the
equivalent of tables in the relational model, and with the individual records being
the equivalent of rows. To create links between these record types, the
hierarchical model uses Parent Child Relationships. These are a 1:N mapping
between record types. This is done by using trees, like set theory used in the
relational model, "borrowed" from maths. For example, an organization might
store information about an employee, such as name, employee number,
department, salary. The organization might also store information about an
employee's children, such as name and date of birth. The employee and children
data forms a hierarchy, where the employee data represents the parent segment
and the children data represents the child segment. If an employee has three
children, then there would be three child segments associated with one employee
segment. In a hierarchical database the parent-child relationship is one to many.
This restricts a child segment to having only one parent segment. Hierarchical
DBMSs were popular from the late 1960s, with the introduction of IBM's
Information Management System (IMS) DBMS, through the 1970s.
Hierarchical database model
In the hierarchical model, data is organized as an inverted
tree. Each entity has only one parent but can have several
children. At the top of the hierarchy, there is one entity,
which is called the root.
Figure 14.3 An example of the hierarchical model representing a university
14.17
Hierarchical Model
Network model
• The network model expands upon the
hierarchical structure, allowing many-to-many
relationships in a tree-like structure that allows
multiple parents.
• Thus all the sets comprise a general directed
graph (ownership defines a direction),
or network construct. Access to records is either
sequential (usually in each record type) or by
navigation in the circular linked lists.
Network Model
•
The popularity of the network data model coincided with the popularity of the
hierarchical data model. Some data were more naturally modeled with more than
one parent per child. So, the network model permitted the modeling of many-tomany relationships in data. In 1971, the Conference on Data Systems Languages
(CODASYL) formally defined the network model. The basic data modeling construct
in the network model is the set construct. A set consists of an owner record type, a
set name, and a member record type. A member record type can have that role in
more than one set, hence the multiparent concept is supported. An owner record
type can also be a member or owner in another set. The data model is a simple
network, and link and intersection record types (called junction records by IDMS)
may exist, as well as sets between them . Thus, the complete network of
relationships is represented by several pairwise sets; in each set some (one) record
type is owner (at the tail of the network arrow) and one or more record types are
members (at the head of the relationship arrow). Usually, a set defines a 1:M
relationship, although 1:1 is permitted. The CODASYL network model is based on
mathematical set theory.
Network database model
In the network model, the entities are organized in a graph,
in which some entities can be accessed through several paths
(Figure 14.4).
Figure 14.4 An example of the network model representing a university
14.21
Relational Model
• The most popular data model in DBMS is Relational Model. It is
more scientific model then others. This model is based on firstorder predicate logic and defines table as an n-ary relation.
• The main highlights of this model are:
• Data is stored in tables called relations.
• Relations can be normalized.
• In normalized relations, values saved are atomic values.
• Each row in relation contains unique value
• Each column in relation contains values from a same domain.
•
Relational Data Model
• (RDBMS - relational database management system) A
database based on the relational model developed by
E.F. Codd. A relational database allows the definition of
data structures, storage and retrieval operations and
integrity constraints. In such a database the data and
relations between them are organised in tables. A table
is a collection of records and each record in a table
contains the same fields.
Properties of Relational Tables:Values Are AtomicEach
Row is UniqueColumn Values Are of the Same KindThe
Sequence of Columns is InsignificantThe Sequence of
Rows is InsignificantEach Column Has a Unique Name
Relational Model
Relational database model
In the relational model, data is organized in two-dimensional
tables called relations. The tables or relations are, however,
related to each other, as we will see shortly.
Figure 14.5 An example of the relational model representing a university
14.27
14.5 THE RELATIONAL DATABASE MODEL
In the relational database management system
(RDBMS), the data is represented as a set of relations.
14.28
Relations
A relation appears as a two-dimensional table. The RDBMS
organizes the data so that its external view is a set of
relations or tables. This does not mean that data is stored as
tables: the physical storage of the data is independent of the
way in which the data is logically organized.
14.29
Figure 14.6 An example of a relation
A relation in an RDBMS has the following features:
 Name. Each relation in a relational database should have
a name that is unique among other relations.
 Attributes. Each column in a relation is called an
attribute. The attributes are the column headings in the
table in Figure 14.6.
 Tuples. Each row in a relation is called a tuple. A tuple
defines a collection of attribute values. The total number
of rows in a relation is called the cardinality of the
relation. Note that the cardinality of a relation changes
when tuples are added or deleted. This makes the
database dynamic.
14.30
14-6 OPERATIONS ON RELATIONS
In a relational database we can define several operations
to create new relations based on existing ones. We
define nine operations in this section: insert, delete,
update, select, project, join, union, intersection and
difference. Instead of discussing these operations in the
abstract, we describe each operation as defined in the
database query language SQL (Structured Query
Language).
14.31
INTRODUCTION TO SQL
Structured Query Language
Structured Query Language (SQL) is the language
standardized by the American National Standards Institute
(ANSI) and the International Organization for
Standardization (ISO) for use on relational databases. It is a
declarative rather than procedural language, which means
that users declare what they want without having to write a
step-by-step procedure. The SQL language was first
implemented by the Oracle Corporation in 1979, with
various versions of SQL being released since then.
14.33
Insert
The insert operation is a unary operation—that is, it is
applied to a single relation. The operation inserts a new tuple
into the relation. The insert operation uses the following
format:
14.34
Figure 14.7 An example of an insert operation
Delete
The delete operation is also a unary operation. The operation
deletes a tuple defined by a criterion from the relation. The
delete operation uses the following format:
14.35
Figure 14.8 An example of a delete operation
Update
The update operation is also a unary operation that is applied
to a single relation. The operation changes the value of some
attributes of a tuple. The update operation uses the following
format:
14.36
Figure 14.9 An example of an update operation
Select
The select operation is a unary operation. The tuples (rows)
in the resulting relation are a subset of the tuples in the
original relation.
14.37
Figure 14.10 An example of an select operation
Project
The project operation is also a unary operation and creates
another relation. The attributes (columns) in the resulting
relation are a subset of the attributes in the original relation.
14.38
Figure 14.11 An example of a project operation
Join
The join operation is a binary operation that combines two
relations on common attributes.
14.39
Figure 14.12 An example of a join operation
Union
The union operation takes two relations with the same set of
attributes.
14.40
Figure 14.13 An example of a union operation
Intersection
The intersection operation takes two relations and creates a
new relation, which is the intersection of the two.
14.41
Figure 14.14 An example of an intersection operation
Difference
The difference operation is applied to two relations with the
same attributes. The tuples in the resulting relation are those
that are in the first relation but not the second.
14.42
Figure 14.15 An example of a difference operation
Object oriented Model
• In the 1990s, the object-oriented
programming paradigm was applied to
database technology, creating a new database
model known as object databases.
• Object databases also introduce the key ideas
of object programming, such
as encapsulation and polymorphism, into the
world of databases.